Cloud/genai Engineer

Elastic Elastic · Enterprise · India · IT

The Cloud/GenAI Engineer will be responsible for architecting, implementing, and scaling cloud-native infrastructure while driving generative AI capabilities. This role combines advanced DevOps engineering with cutting-edge AI infrastructure management, focusing on building resilient, scalable cloud platforms to support internal systems and GenAI applications.

What you'd actually do

  1. Develop comprehensive infrastructure as code using Terraform, including custom providers and modules
  2. Implement configuration management using Ansible, including custom roles and playbooks
  3. Create automated deployment pipelines with advanced CI/CD practices (GitOps, trunk-based development)
  4. Design and implement infrastructure testing frameworks and validation procedures
  5. Implement comprehensive observability solutions using the Elastic Stack

Skills

Required

  • Terraform
  • Ansible
  • CI/CD
  • Kubernetes
  • AWS
  • Azure
  • GCP
  • Docker
  • HashiCorp Vault
  • cert-manager
  • GitOps
  • Elasticsearch
  • Kibana

Nice to have

  • custom providers and modules
  • custom roles and playbooks
  • GitOps, trunk-based development
  • infrastructure testing frameworks
  • log aggregation and analysis
  • security controls and compliance measures
  • custom resource definitions (CRDs) and operators
  • HPA/VPA, network policies, and pod security policies
  • container image build pipelines
  • multi-region Kubernetes clusters
  • service mesh architectures
  • Microsoft Cognitive Services
  • TensorFlow
  • PyTorch
  • Hugging Face Transformers
  • CloudFormation
  • ARM templates
  • Salt
  • overlay networks
  • VPC configuration and management
  • load balancing
  • ArgoCD
  • Flux
  • Jenkins
  • GitLab CI
  • GitHub Actions
  • advanced Git workflows
  • application and service configurations
  • index lifecycle policies
  • query optimization
  • dashboard automation and templating
  • model deployment and automation
  • ethical AI practices
  • responsible AI development

What the JD emphasized

  • Proven experience in developing generative AI models
  • Proficiency in deep learning frameworks such as Microsoft Cognitive Services, TensorFlow, PyTorch, or Hugging Face Transformers
  • Hands-on experience with Elasticsearch, including cluster management, index lifecycle policies, and query optimization.

Other signals

  • GenAI roadmap
  • AI strategy
  • AI infrastructure
  • generative AI capabilities
  • GenAI applications